Methods and systems for measuring and improving a sleep environment

ABSTRACT

Computer-implemented methods for recommending a sleep-aid product for a user are provided. In the methods, a user&#39;s sleep is monitored to obtain monitoring data, which are analyzed and at least one issue is identified with the user&#39;s sleep. A recommendation is provided to the user to address the issue. Systems and devices for implementing the methods are also provided.

BACKGROUND OF THE INVENTION

The present invention relates to sleeping aids, and more particularly, to methods and devices to monitor and manage a user's sleep.

A prevalent and often overlooked cause to many secondary health and social problems is insufficient and/or poor-quality sleep. Estimates show that that 65% of the population has at least a few nights a week suboptimal sleep. Humans require considerable rest each night and if the sleep is broken, brain function, problem-solving, cognitive skills, and reasoning are affected. Other potential consequences of insufficient sleep include short and long-term memory loss, mood changes, a weakened immunity, high blood pressure, weight gain, insulin control, which increases the risk for Type 2 diabetes, heart disease, poor balance, and a lower sex drive. Insufficient and poor-quality sleep will also affect a person's work performance, and likely disrupt their social behavior and social interactions, potentially damaging relationships.

Various methods of improving a person's sleep include physical exercise, breathing exercises and optimizing the user's ambient conditions such as music, light, temperature etc. A variety of monitoring and sleep improvement products have been (or are) on the market, including wearable devices such as wristwatches, armbands, head mounted devices, and non-contact products.

It is an object of the present invention to provide methods and devices to monitor sleep behavior and manage sleep which overcome the deficiencies of the prior art.

SUMMARY

The present invention provides devices, systems, and computer-implemented methods relating to measuring, analyzing, managing and/or improving sleep and/or the sleep environment. The sleep management aspects are derived from the personal situation of the user and will provide personalized strategies to improve sleep rather than generic tips. In some aspects, the disclosure concerns sleep improvement products and sleep environment optimization rather than behavioral change of the sleeper, which is more the common starting point for personalized sleep improvement.

In one aspect, the present invention provides a computer-implemented method for recommending a sleep-aid product for a user, the method comprising: monitoring the user's sleep to thereby obtain monitoring data; by using at least one computer processor, analyzing the monitoring data and identifying at least one issue with the user's sleep; and by using at least one computer processor and based on the analysis, providing a recommendation on a sleep-aid product for the user on an electronic device user interface that addresses the at least one issue.

In some embodiments of the method, analyzing the monitoring data comprising determining the effect of one or more products being currently used by the user on the user's sleep.

In some embodiments of the method, the method further comprises: monitoring the user's sleep for a preset period of time after the user starts using the recommended sleep-aid product to obtain updated monitoring data; by using at least one computer processor, analyzing the updated monitoring data; based on the analysis and by using at least one computer processor, determining the effect of the recommended sleep-aid product on the user's sleep.

In some embodiments, the recommendation is based on databases containing products and their alleged benefits on a user's sleep.

In some embodiments, the method further comprises: providing one or more questions for the user to answer regarding the user's experience with the use of the recommended product, and receiving a response from the user; wherein the determination is further based on the user's response.

In some embodiments, the method further comprises: generating, using at least one computer processor, a quantitative effectiveness score for the recommended product based on the monitoring data. The method can further comprise: generating, using at least one computer processor, an overall effectiveness score for the recommended product based on both the monitoring data and the user's response. Generating the overall effectiveness score can comprise discounting the user's response distorted by secondary factors not directly relating to the performance of the recommended product.

In any of these embodiments, the monitoring the user's sleep can include monitoring the user's body movements during the sleep, and/or monitoring an environmental condition during the user's sleep in the room where the user sleeps. The method can further comprise uploading the monitoring data to a remote server.

In another aspect, the present invention provides a computer-implemented method for evaluating the effectiveness of a sleep-aid product for a user's sleep, the method comprising: monitoring the user's sleep to thereby obtain monitoring data, wherein during the user's sleep the sleep-aid product is being used; by using at least one computer processor, analyzing the monitoring data with respect to a known issue of the user's sleep; and based on the analysis and by using at least one computer processor, determining the effectiveness of the sleep-aid product on addressing the issue in the user's sleep.

In some embodiments, the method further comprises: monitoring the user's sleep before the user uses the sleep-aid product to obtain first collected data; wherein determining the effectiveness of the recommended sleep-aid product is at least partially based on comparing the monitoring data with the first collected data.

In a further aspect, the present invention provides a method of determining an effect of a first person's sleep on his or her sleep partner's sleep, the method comprising: recording the movements, temperature and sounds from a bed where the first person sleeps on during the first person's sleep using a monitor device positioned in the bed, without the sleep partner's presence in the bed with the first person. The monitor device can be disturbance measuring device which comprises: a processor; a memory operatively coupled to the processor; an accelerometer for measuring vibration; a thermometer; a microphone; optionally a speaker; and a light sensor for sensing ambient light.

In a further aspect, the present invention provides a computer-implemented method of testing a first mattress, the method comprising: positioning a disturbance-measuring (DM) device on a side of the first mattress; recording, using the DM device, data relating to movements of a user on the first mattress according to a preset series of actions relevant to the use of the mattress during his or her sleep; and analyzing, using at least one processor, the recorded data using at least one processor to thereby obtain an evaluation of the first mattress in terms of its performance in the potential disturbance of the sleep of a sleep partner of the user by the user. In some embodiments, the method further comprises: positioning a DM device on a side of a second mattress; recording, using the DM device, data relating to movements of the user on the second mattress according to a same preset series of actions; comparing the recorded data for the second mattress with the recorded data for the first mattress, to thereby determine a similarity between the first mattress and second mattress with respect to their performance in potential disturbance of the sleep of a sleep partner of the user by the user.

In a further aspect, the present invention provides a computer-implemented method for evaluating the effectiveness of a sleep-aid product for a user's sleep, the method comprising: monitoring the user's sleep to thereby obtain baseline monitoring data; determining when the user has acquired and started using a new sleep-aid product; monitoring the user's sleep while the new sleep-aid product is being used, to thereby obtain updated monitoring data; and by using at least one computer processor, comparing the updated monitoring data with the baseline monitoring data, to thereby determine the desirability of the sleep-aid product. In some embodiments, determining when the user has acquired and started using a new sleep-aid product comprises: tracking the user's online purchase history. In some embodiments, determining when the user has acquired and started using a new sleep-aid product comprises: presenting one or more questions to the user on an electronic device user interface and receiving the user's response thereto.

In a further aspect, the present invention provides a system or a monitor device comprising a computer processor and an associated memory, where the memory stores instructions which when executed by the processor, enable the system or monitor device to perform the various embodiments of the methods as described herein.

In a further aspect, the present invention provides a tangible computer-readable storage medium which include a computer program product (or software), which when executed by a processor, enable a device or system to perform the various embodiments of the methods as described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic of a sleeping monitor, according to one embodiment of the present invention;

FIG. 2 is a perspective view of an exemplary bedroom, showing a bed, a user sleeping in the bed, a side table and a sleeping monitor, according to another embodiment of the present invention;

FIG. 3 is a perspective view of a bedroom showing a bed with two users sleeping thereon, and a sleeping monitor having angularly displaceable radar transducers, according to some embodiments of the invention;

FIG. 4 is a perspective view of a bedroom showing a bed and a headboard with two users sleeping thereon, and a sleeping monitor attached to the headboard, according to some embodiments of the invention; and

DETAILED DESCRIPTION

The present disclosure provides systems, computer readable storage media, computer-implemented methods, software application program adapted to operate on portable electronic devices, e.g., a smart phone or a personal monitor, or a server or cloud, for analyzing, managing, and improving a user's sleep. As used herein, the term “user” refers to a person or individual.

Every person is different, and as such, each person requires that a unique set of conditions be met before a good night sleep is achieved. For some people, getting to sleep and sleeping well through the night is not a problem and sleeping conditions that would generally be considered adverse to most people appear to be accepted and ignored by this group. With others however, a combination of sleeping conditions and preferences must be met each night, with little exception, or the person's quality of sleep will attenuate and his or her sleep will take much longer to reach at the start. Some people cannot sleep unless the window is open, while others need to have the bedroom completely dark. Others still need to hear music on very low volume as they lay down for sleep. Other issues relate to a person's diet. For example, spicy foods consumed during dinner may upset a person's stomach at bedtime and disrupt his or her normal sleep behavior. In contrast, certain other foods may promote a person to sleep more quickly and more deeply. Physical exertion by a person throughout the day may affect people's sleep differently, depending on the duration, type and intensity of the particular exercise or activity. Some people sleep better after a long run in the morning, while others become energized all day and have trouble sleeping at night. Other considerations which may affect the sleep quality of a person include the type of sleep-related products the particular person uses. For example, most people are intimately attached to the type of pillow they use for sleep. Some must have a firm pillow to support their neck, while others swear by a softer pillow that perhaps helps keep a cool surface for their head.

The sleeping environment, a person's diet, his or her level of stress, and level of exercise, and the type of sleeping-related products they use all may contribute how well a person sleeps each night.

Many factors of a bedroom environment can be controlled. For example, by opening a window, introducing air conditioning, or using a humidifier (or dehumidifier) to help control the level of moisture in the air, the air quality of a bedroom may be controlled. Sound generators, such as a radio, television, or so-called noise generators may be used in a bedroom to immerse a person in music, broadcast news, or perhaps an acoustic world of jungle parrots, distant thunder, or the babble of a New England stream. Illumination may be controlled by introducing mood lighting, or using so-called “blackout” shades to effectively prevent any light from entering into a bedroom from a window.

Products to help aid in a person's sleep are continuously being designed and manufactured, including new types of mattresses that provide full body support, sheets that stay cool, pillows that support a person's head and neck, and may other products and devices.

Regardless of what a person does to help his or her sleep, it is important to carefully monitor the person's sleep to determine how effective the particular change actually is.

The present invention provide system and device for collecting sleep-related data (continually or periodically according to certain schedule) from its users or subscribers, along with profile information of each user. The profile information collected includes information such as, a user's age, gender, weight, height, occupation, quantity of drinking and smoking and other health details, level of exercise, typical bedtime and wakeup time, and general diet details. Subscribers to the present system use a monitor device which carefully tracks minute movements and sounds of the user before and during sleep. Every day the collected data from each monitor is uploaded to the present system's central database. The uploaded data and is then used to assess the quality and duration of the user's sleep and provide recommendations, should any poor-sleep events or habits be detected. The present system, according to one embodiment of the invention, acquires data of an ever-growing number of users. The present system can use this data to help predict and/or help establish the effectiveness of a particular sleep aid, or condition, based on certain parameters of a particular user, as described in greater detail below.

The present invention also provides systems, devices and methods to predict and/or help establish the general effectiveness of a particular sleep aid (i.e., a device or product that is meant to benefit a user's sleep quality). Such aids may include bedding, pillows, mattresses, toppers, neck support devices, air purifiers, air conditioners, illumination devices, sound generators, snoring cessation devices, and others. The system can initially accept known ratings of various sleep aids by accessing databases which include established research data and qualified user ratings of a particular sleep aid (such as Amazon's review listings of a particular product). Then the system can use word recognition techniques to help categorize reviews from users of the particular product, such as locating the term “sore neck” in connection with a low star rating of a particular support pillow may mean that the pillow may not be effective at supporting the user's neck. Eventually, the present system will collect sufficient data of products being used by its subscribers to establish its own rating of each product, linking the pros and cons of each product to specific parameters of specific users regarding specific sleep disorders and conditions.

Based on this collected data of various products, the system of the present invention can recommend a particular sleep aid on an electronic device user interface to a particular subscriber of the present system (a user) based on measured criteria. For example, the present system may monitor a male subscriber as he sleeps and learns over a period of time that he moves his arms and head regularly for at least 30 minutes before entering a first sleep stage, wakes up with a stiff neck and is not getting enough sleep for his age and activity levels. The present system uses this information and compares these movements to similar ones in the present system's database. Based on common matches from the database search, the present system, continuing with this example, determines that the user's pillow is likely too thin or too soft to support the user's head sufficiently and recommends to the user that he replaces his current pillow with a particular brand of pillow that has been determined (based on collected review data and perhaps clinical research data) to be thicker and stiffer and better for supporting the head and necks of men of a certain age, height and weight.

As used herein, an electronic device user interface includes a typical graphic user interface of an electronic device (e.g., a monitor device, smart phone, or other smart devices) which displays visual information to the user, as well as other ways to communicate to the user, such as vibration, audio, light and other signals that can be perceived by the user.

Continuing again with this example, the system of the present invention can determine that the user has followed the system's recommendation (as described in greater detail below) and replaced his pillow with the recommended product. The system will then associate with the new product newly acquired sleep data from monitoring the user and will evaluate newly collected results accordingly. The product will be accessed and its rating possibly revised based on the outcome of the newly collected data. If the particular user is monitored as having a higher sleep quality, or if particular aspects of the user's sleep have improved after using the particular recommended product, then the product will thereafter be associated with the improvement and its effectiveness rating at improving overall sleep of a user or at least improving certain aspects of a user's sleep, will increase.

The present system can also acquire valuable feedback from the user regarding the new pillow and will collect this data to continually revise and update the ratings of the particular pillow product, and additionally, associate the product with details regarding how it affected users' sleep and the profile and personal details of any particular users (age, weight, height, smoker, etc.). This information can be continuously updated to strengthen the system's capabilities to accurately assess and correct specific sleep-related, issues, disorders and conditions and increase a user's overall sleep quality (or sleep score).

The system of the present invention can access databases of known products on the market having internal ratings. The present system begins with defined basic categories and a baseline set of rated products within each category. For example, a category called “stiff necks” may include several different types of commercially available supportive pillows and neck supports and perhaps certain treatments to aid in people having stiff necks. As described above, the system can utilize known effectiveness data from outside sources as a baseline and revise ratings and reviews as the products are field tested by trusted subscribers of the system. If a particular product does not have any rating information, or fails to meet a minimum threshold of ratings, the product is considered “unproven” and will be recommended only after other more-proven products have been first tried to overcome a particular sleep issue. Eventually, the present system will have collected sufficient trusted user-data for such otherwise unknown or unproven products, thereby providing a trusted rating value for the same.

Until the present system is able to accumulate effectiveness ratings of products based on trusted field testing of subscribers to the present system and collected feedback and analyzed sleep data from its users, the present system preferably uses popular sleep aid products within core categories, such as mattresses and pillows, and subcategories, such as memory foam mattresses and neck-supporting pillows. Such popular products are more likely to have a higher number of ratings, of which most will be reliable and accurate. This information may be supported by validation studies conducted by the product company for determining the efficacy of targeted products. The information from these studies is used to establish a clear baseline on the impact on a prospective user of the product. The information will also provide clues as to how the particular product may benefit a user's sleep and provide supplemental information.

Over time, as the present system aggregates more and more trusted user data regarding specific sleep-aid products (and services and medical treatments) and how each product is effective at correcting specific sleep-related disorders (issues) or conditions, additional categories and subcategories may evolve. The system may use any appropriate algorithm to generate an effectiveness score for each product based on user review and collected sleep data. For example, a user is given a product recommendation to overcome a specific sleep-related issue. The present system uses methods described below, according to other embodiments of the invention, to establish that the user is indeed using the recommended product as he or she sleeps. The system automatically collects sleep monitoring data of the user to determine how well the recommended product performs in correcting or at least mitigating the specific sleep issue. The system can use collected sleep data to calculate a percentage of improvement of the particular sleep issue. Perhaps over a period, such as two weeks, the data shows that a particular exemplary user “tossed and turned” for an average of 50% less time prior to reaching a first stage of sleep after using a recommended “cooler” pillow. In this case, the particular pillow could be given a quantified effectiveness value of “5” (out of 10). After a predetermined period of time (such as two weeks), the user would be asked a few questions regarding the particular recommended product to establish a qualitative effectiveness score to supplement quantitative collected objective sleep metrics. Examples of such questions could include:

-   -   1) “Since using our recommended Cooler Pillow product, beginning         Two Weeks Ago, please answer the following questions regarding         your recent Neck-Strain issue (Using a scale between 1 and 10,         where 1 is poor, and 10 is great):         -   a) How does your new product make you feel during your             sleep?             -   1 2 3 4 5 6 7 8 9 10         -   b) Do you feel rested when you wake up?             -   1 2 3 4 5 6 7 8 9 10         -   c) Does your neck feel sore when you wake up?             -   1 2 3 4 5 6 7 8 9 10         -   d) Do you feel like you fall asleep faster?             -   1 2 3 4 5 6 7 8 9 10         -   e) Do you feel like you have more energy during the day?             -   1 2 3 4 5 6 7 8 9 10                 Other questions may include:     -   2) Where did you purchase the recommended product?     -   3) How much did you pay for the recommended product?

The present system can use the responses from the such questions to generate a qualitative-effectiveness score of the particular recommended product. The quantitative-effectiveness score and the qualitative-effectiveness score may be used to establish an overall-effectiveness rating for the product regarding overall sleep and the specific sleep-related issue. According to the present invention, other information about the particular product, such as price and availability may be used in calculating the above overall-effectiveness rating.

According to the present invention, should a user not provide any answers to product-review questions, as shown above, or if the answers to the questions are suspected of being inaccurate, such as always receiving 10s or 1s from a particular user, then the qualitative-effectiveness score may be ignored, resulting in the present system relying solely on the quantitative-effectiveness score in calculating the overall-effectiveness score of the product. Perhaps in such instance, the rating score is weighted accordingly, such as by 50%.

The above-described product-review questions can be provided to each user using a web-based software program operating on the user's portable smart device, such as a smartphone. The program preferably measures the amount of time it takes for each question to be answered to help establish a level of authenticity in the user's response. For example, a question requires an average of 12 seconds to read, and an average of 10 seconds to answer, as determined by collected data of actual users, and/or independent testing. If, in such instance, a particular user answers the question in less than 5 seconds, then, according to the invention, it can be assumed that the user has not read the question and lacks sincerity in participating in the survey. In this case, the present system would ignore the response from the user for either that question, or all the questions, since the user is likely not (and will not be) authentic and honest in his or her response. If the user provides an unrealistic time to answer two questions concurrently, the present system can immediately end the survey. Also, the present system preferably “times out” after a predetermine amount of time spent answering any particular question, such as 1 minute, after which the present software program, according to the invention, can ask the user if he or she requires additional time to answer the question. If no response is detected (after a predetermine amount of time), the present software program preferably ends the survey. The purpose of this feature is to help ensure that only authentic, honest and accurate product review responses are received and approved.

The present system, according to the invention, can ask the user details about any recommended products sometime after the user trial period has elapsed, perhaps after two weeks or one month of use. One line of questions which may be asked of the user is the price paid for the product. Was the product a gift, or otherwise free? Was the product very expensive? The system may compare the user's answer with an average of known prices collected from various sites on the Internet.

This is an important question since the price and the brand name of the product may introduce a psychological component of “perceived value,” wherein the user may assume that since he or she paid so much for the costly product, it must be working. Products with prices above/below a certain threshold may suffer from an adoption perception curve, e.g., “My expensive mattress can do no wrong.” OR “This cheap mattress could never give me a good night sleep.” Products can be tagged and monitored for this potential influencing factor. If confirmed, the present system can actively work against distorted perception by asking the user similar questions multiple times to draw an average response or to use other methods of extracting truth from a subject that may be knowingly or unknowingly distorting their answers from the absolute truth.

Alternatively, the present system can consider a) such secondary influences (price paid, brand recognition, popularity, etc.), b) a user's responses to qualitative questions regarding the assessment of a particular product's effectiveness (see above), and c) measured data collected from the monitoring device to determine if secondary influences affected the user's perception of product effectiveness. If it is determined that the purchase price, the brand name, or some other secondary influencing factor affected the authenticity of a user's response in evaluating the effectiveness of a product, the system may decide to apply a weighting factor to the measured data collected automatically by the monitoring device. This decision may be based on degree of disparity between the measured values of quantitative-effectiveness and received values of qualitative-effectiveness from the user.

For example, a user is following a system recommendation and purchased a brand name and popular memory-foam mattress at full price at a store (considered by the present system to be an above average price). The user uses the new mattress for one full month and then is asked by the present software program, initiated by the present system to answer qualitative questions regarding the new mattress. The user gave the new product high marks for all questions. However, continuing with this example, the monitoring device used to monitor specific movements by the user, as he or she slept, detected user-movements which indicated a restless sleep, with numbers worse than before the purchase of the new mattress, indicating that the quantitative-effectiveness values of the new mattress are much lower than the values of qualitative-effectiveness. This disparity suggests that the user doesn't know or doesn't want to admit to how bad they really slept. In such instance, the present system would assume that secondary factors influenced the user's perception of the quality of sleep achieved by the new mattress. The system, in this example, would ignore the qualitative-effectiveness results and rely solely on the more reliable quantitative-effectiveness results.

The present system can recognize that certain product categories may require different amounts of usage before their effectiveness may be accurately evaluated. For example, a new mattress product may require that a user sleep on it for two or three months before its effectiveness may be determined. In contrast, a pillow product may only require a week. The present system can establish the appropriate amount of time for each product by category, cost, effort required to replace or return, and other factors. Also, the testing period may be ongoing so that a product's effective life may be accurately measured. For example, a firm neck-supporting pillow may be very effective for the first six months, but may lose its support slowly after that. The present system can detect when a product becomes less effective and can alert the user when the product fails to maintain good quantitative-effectiveness values, which are measured constantly. Any collected user data can be provided to the product companies for internal product evaluation, engineering review and product development. The fact that sleep-aid products used by users of the present system are effectively field-tested by actual customers in real-life environments can only increase the reliability of the resulting data and feedback.

As mentioned above, the present system preferably determines the quantitative-effectiveness value of a product based on user-movement measurements made by the monitoring device. It should be noted that any type of sleep-monitor may be used with the present system to monitor a user and provide sleep-related data, regardless of how the other sleep monitors operate, and the type of data provided. The processes and methods used in the present system, described herein are measuring-device agnostic and any of many types of sleep-monitor data may be used to carry out the various features and embodiments of the present invention, described herein. Other sensors may be used to measure other factors which may help determine the quality of a user's sleep using a new product. Such factors include movement of user during sleep, temperature of user during sleep, noise from user during sleep, duration of overall sleep, duration of specific sleep stages, time between user going to bed and falling asleep, wake-up time, etc.

A method for evaluating the effectiveness of a sleep-aid product, according to the invention, includes the steps of:

1) Using a body-displacement measurement device, measure body movement of a sleeping user and determine a first level of sleep quality of the user using a first sleep-aid product, collect and store the data as first monitored data;

2) Replacing the first sleep-aid product with a second sleep-aid product.

3) Using a body-displacement measurement device, measure body movement of the same sleeping user and determine a second level of sleep quality of the user using the second sleep-aid product, collect and store the data as second monitored data;

4) Comparing the first collected monitored data with the second collected monitored data;

5) Using the comparison information to determine the effectiveness of the second sleep-aid product based on the first sleep-aid product; and

6) Repeating steps 1-5 for the person sleeping different nights;

7) Repeating steps 1-6 for different people to confirm results; and

8) Using the first and second collected data to support the return of the second sleep-aid product or the certification of the second sleep-aid product as being effective, depending on the results.

After the above-listed second step, a step of detecting (automatically or manually) the second sleep-aid product may be included, according to the present invention.

According to certain embodiments of the present invention, a user may follow the recommendation of a sleep-aid product by the present system. The user would confirm purchase of the product and provide purchasing details, such as brand name, price and location of purchase. The present system can use this information to determine product warranty details, such as the time period for return of the product due to a user being unsatisfied, and use this information to help remind a user of the return deadlines. The present system can further suggest that a user returns a product based on an indication of poor quantitative-effectiveness values calculated since use of the new product commenced compared to quantitative-effectiveness values calculated before the new product was first in use. The present system collects data of each user's sleep data (such as sleep quality score) before and after a new product (such as a mattress) is purchased and used. The user therefore has sleep history data to substantiate a product return claim, or to provide valuable user feedback to the company of the particular product.

In some embodiments, the present system may be set up to post a user's feedback regarding a particular product directly to a select website, or multiple websites, such as the website of the particular product, or an online retailer's website. Alternatively, companies of products may pay to access and repost select user reviews of their product from the present system. Also, a subscribing user can be given access to a community of users, such as a chat or forum, covering many products. The access given may be to information relating to all products, select products, or only products that have been or are being used by the user. The accessible information preferably includes details of sleep-aid products, how they performed, reviews and ratings, and which sleep-related issues the products may or may not help overcome.

A company of a product may request use of the present system to initiate a product review by leveraging the subscribed users of the present system. Based on the independent reviewing process of the present system, both qualitative and quantitative effectiveness values may be calculated and collected over a prescribed testing period. Depending on the test results, the product may receive a “certification of sleep-effectiveness” by the present system. The product company may then use this certification in their marketing of the particular product. Also, the test results may offer the company suggestions for improving the product, or developing others. For example, a pillow company requests the use of the present system for testing a newly developed memory-foam pillow that provides adjustable neck support. The test results, in this example are promising with over 300 positive reviews and high quantitative-effectiveness scores. The qualitative-effectiveness scores are also high, but many of the respondents indicated negative ratings for cleaning the pillow. Apparently, in this example, the pillow case was difficult to remove from the pillow structure. The company learns from these comments and decides to perform a running-redesign to overcome this apparent deficiency. User testing and user feedback is invaluable.

Referring to FIG. 1, and according to some embodiments of the present invention, a block diagram schematic of an example sleep monitor 10 (also referred to as a monitor device in this disclosure) is shown including a computer processor (or simply a processor, or CPU) 12, a power supply 14, a Bluetooth/WIFI communication circuit 16, a memory 18. The monitor device can have an architecture of a general purpose computer, where different components can communicate through a system bus. As can be appreciated by those skilled in the art, processor 12 is connected to all components and controls the operation of each. Bluetooth/WIFI communication circuit 16 includes conventional communication circuitry to allow selective communication with Bluetooth and WIFI devices, including a Home Area Network 22, which in turn is connected to the Internet 24. The Bluetooth/WIFI communication circuit 16 includes the use of all types of wireless communication devices and techniques, such as, but not limited to Bluetooth, WIFI, and Zigbee. In addition, as illustrated in FIG. 1, a radar transducer 20 (e.g., a Doppler type) is shown. It is understood that other types of motion sensors may be used in place of a radar transducer, including, but not limited to SONAR (using sound waves to detect micro displacements), and LIDAR (wherein light is used to deter micro displacements) and IR sensors. The term “radar” and “radar transducer” is used hereinafter to include all types of motion detection and displacement measuring devices.

The diagram shown in FIG. 1 is only a non-limiting example of a “sleep monitor” or “monitor device” (or simply “monitor”) as used in this disclosure. This disclosure contemplates any suitable “sleep monitor” or “monitor device” having any suitable number of any suitable components in any suitable arrangement. It is understood that a “sleep monitor” or “monitor device” can broadly encompass all monitoring devices or systems that can sense or monitor environment conditions (ambient temperature, humidity, sound, vibration, lighting, air quality, etc., of the environment in which the subject person is being monitored) as well as physiological and/or biomechanical signals from a human body (e.g., body movement, noise made by the person, body temperature, breathing, heartbeat, cardiogram, brain activity, etc.), by an either contact or non-contact manner. A monitor device can include all components and functionalities of a general smart phone (e.g., speaker, microphone, camera, GPS, accelerometer, etc.) as well as sensors and other components (e.g., radar/sonar related components) that are typically not included in a general smart phone. The software program of the present invention can be installed/loaded directly in the monitor device(s) to process information and data gathered by the sensors and other signal-acquisition components as well as other data entered by the user or retrieved from other sources. Alternatively, if the monitor device does not include the advanced chips/memory or other components of modern-day smartphones, the monitor device can be configured to work in concert with such a smartphone and utilize the components available on the smartphone (e.g., a microphone or other sensing devices), and in which case, the present software program can also be loaded on the smartphone which can be used to process information received from the monitor device. In some instances, the user's smart phone or other portable or wearable smart devices can be deemed standalone monitor devices.

In the sleep monitor or the monitor devices described herein, the processor can include one or more processors, which can include hardware for executing instructions, such as those making up a computer program or application, for example, it may retrieve (or fetch) the instructions from an internal register, an internal cache, memory, storage; decode and execute them; and then write one or more results to internal register, internal cache, memory, or storage. In particular embodiments, software executed by processor may include an operating system (OS). As an example and not by limitation, then the OS may be a mobile operating system, such as for example, Android, iOS, Windows. In some embodiments, the memory can include main memory for storing instructions for the processor to execute or data for processor to operate on. One or more buses may connect the processor with the memory. The memory can include random-access memory (RAM). This RAM may be volatile memory, where appropriate. Where appropriate, this RAM may be dynamic RAM (DRAM) or static RAM (SRAM). The monitor device can further include a permanent data storage device which can include non-volatile and/or non-transient mass storage or media for data or instructions, for example HDD, flash memory, optical medium, DVD, etc., or a combination of two or more thereof, solid-state memory, read-only memory (ROM), or any other suitable physical form. The communication component can include hardware, software, or both providing one or more interfaces for communication (such as, for example, packet-based communication) between the monitor device and other devices, for example, a network interface controller (NIC) or network adapter for communicating with an Ethernet or other wire-based network or a wireless NIC (WNIC), wireless adapter for communicating with a wireless network, such as for example a WI-FI network or modem for communicating with a cellular network, such as third generation mobile telecommunications (3G), or Long Term Evolution (LTE) network, wireless PAN (WPAN) (such as, for example, a BLUETOOTH WPAN), a WI-FI network, a WI-MAX network, a cellular telephone network (such as, for example, a Global System for Mobile Communications (GSM), 3G, or LTE network), or other suitable wireless network or a combination of two or more thereof. The bus can include hardware, software, or both coupling components of the personal computing device to each other, for example, a graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a front-side bus (FSB), a HYPERTRANSPORT (HT) interconnect, an Industry Standard Architecture (ISA) bus, an INFINIBAND interconnect, a low-pin-count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a serial advanced technology attachment (SATA) bus, a Video Electronics Standards Association local (VLB) bus, or another suitable bus or a combination of two or more of these.

As used herein, a system of the present invention can include one or more monitor devices described herein, wherein a memory is installed or stored which computer program product(s) (or software), which when activated or running (e.g., executed by the processor), enables the monitor device(s) to perform certain functions or methods according to the instructions of the computer program product. In some embodiments, when the software on a monitor device is activated (the details of which will be further described below), a user interface (UI), or graphical UI, may be loaded on a display area of the device so as to display information to a user and allow a user to interact with the software, e.g., through areas of a touchscreen designated in the computer software. The system can further include other devices that communicate with the monitor devices, e.g., a user smartphone, a remote server, a smart IOT device, a device designated to perform specific analysis (such as detection of certain chemicals), where the present software application product or components thereof can be installed to perform the functions contemplated, or data inputted or gathered by such devices can be sent to a monitor device or another device or server which may act as a nerve center to control or coordinate the functions of all involved devices. The functions and methods to be performed by the software product and the system are further described herein.

As shown in FIG. 2, monitor 10 is positioned in a user's bedroom, next the user's bedside, such as on the user's side table 30. Doppler radar transducer 20 is directed towards a user 32 as he or she sleeps in a bed 33. Radar transducer 20 is designed to transmit and receive radio waves of a specific frequency to measure minute displacements of user 32 as he or she sleeps, including the subtle movements of breathing, snoring and muscle contractions (twitching). The received signals are collected and stored as data in local memory 18 and eventually, at prescribed intervals, the data from memory 18 is uploaded to a remote server using the Bluetooth/WIFI communication circuit 16, as controlled by onboard processor 12, and any other necessary appropriate known communication method.

As shown in FIG. 1, other types of sensors (called auxiliary sensors), according to this invention may be included with the automatic sleep monitor 10. Such auxiliary sensors may include a thermometer 25 for measuring bedroom temperature, a light sensor 26 for measuring any light in the bedroom, a microphone 27 for measuring sounds that can be heard in the bedroom. The data collected from these auxiliary sensors 25, 26, 27 is combined with the data from radar transducer 20 and time-stamped by processor 12 so collectively, the data from different types of sensors may be analyzed concurrently, locally, using processor 12, or at a later time, using either local processor 12, or a remote server (not shown). In this manner, additional factors of a user's sleeping environment may now be considered when analyzing a user's sleep behavior and generally, as in many fields of study, the more information, the better. For example, if the collected data of a certain user shows sudden body movement by the sleeping user at around 4:15 AM every Monday morning, the data from microphone 27, light sensor 26, and thermometer 25 can then be reviewed for clues at what is happening at that time. Perhaps in this example, the microphone data reveals the distinct sounds of a garbage truck outside picking up the trash at this exact time. Based on this, the user would be given a recommendation to either wear ear plugs on Mondays or perhaps have double-pane windows installed.

According to the present invention, such auxiliary sensors 25, 26, 27 may be used to detect conditions within the user's bedroom. Processor 12 of monitor 10 may be used to determine if any measured parameter or condition within the bedroom exceeds a predetermined value. In such instance, the user can be informed and corrective measures suggested automatically. For example, if the illumination level in the bedroom is measured by light sensor 26, and the value exceeds a certain predetermined level (as decided by the user or as determined using historical data of the user's bedroom), the present system will inform the user (either by text, email, or through the present software program) of the excessive light condition. In this example, the present system will provide an appropriate suggestion to the user, such as turning off all lights before going to bed, providing a sleep partner with a book-light, if appropriate, using an eye mask, or installing blackout blinds to prevent light from entering the room through windows. If loud sounds are detected in the bedroom at bedtime or during sleep time, the present system may suggest that the user locate the source of the sound and try to eliminate it. If this is not possible, the present system will suggest that the user use ear plugs or an appropriate sound-cancelling device.

According to another embodiment of the invention, referring to FIG. 3, a monitor 200 is includes two separately moveable Doppler radar transducers 202, 204 (or other similar movement sensors), one for each person 206, 208 in a bed 210. The above-described calibration techniques can be used to focus each transducer on each respective partner sleeping in bed 210. Monitor 200, with its dual transducers 202, 204 may be positioned at either side of the bed, on a bedside table 212 with one transducer 202 being located above the other 204. The higher transducer 202 is used to monitor the more distant partner, since this higher transducer must “see” over the closer user. The lower transducer 204 may monitor the closer partner in bed.

According to another embodiment of the invention, referring to FIG. 4, a monitor 220 may include appropriate fastening hardware (not shown) to allow the monitor to be mounted on a headboard 222 of a bed 224 (in the center). Monitor 220 may also similarly be mounted to a wall (not shown) adjacent to the headboard, on the ceiling (not shown) over bed 224, or on other walls (not shown) of the bedroom, as appropriate. In the case of mounting monitor 220 on headboard 222 of bed 224, as shown in FIG. 4, a left-side radar transducer 226 is positioned within monitor 220 and is aligned to monitor a left-side user 228 (a user sleeping on a left-side of bed 224), covering a left field of view 230. Similarly, a right-side radar transducer 232 is positioned within monitor 220 and is aligned to monitor a right-side user 234 (a user sleeping on a right-side of bed 224), covering a right field of view 236. Monitor 220 preferably otherwise operates in a similar manner to monitor 200, described above. By having the monitor located symmetrically and above both sleeping users, the respective left and right radar transducers 226, 232 will have a clearer field of view of left and right users, 228, 234, as shown in FIG. 4. Monitor 220 preferably includes two directional microphones (not shown), one for each sleeping user. It may also include a single thermometer and light sensor. Monitored user data of both radar transducers may be stored together in a single memory, but kept separate, as understood by those skilled in the art.

Additionally, a displaceable single Doppler radar transducer (not shown) may be provided in combination with an appropriate drive mechanism (not shown) to allow for controlled and selective angular displacement of the transducer between two or more positions. The monitor here will allow a controller to selectively move the single transducer at prescribed times between a first position to focus on and monitor a first user in bed, and a second position to focus on and monitor a second user in bed. The monitor would continue to move the transducer between the two positions so that both people in bed can be effectively monitored throughout the night, albeit alternately.

According to yet another embodiment of the invention, a disturbance-measuring (DM) device is used to determine how much potential disturbance a sleeping partner inflicts on a sleeping user during a sleeping period (though the night). In some examples, the DM device does not need to be a stand-alone device, but can be regarded as a component for receiving and transmitting input signals to a main monitor device, via an API and/or wired or wireless connection. In other examples, the DM device can be small, self-contained and self-powered with an appropriate internal battery, and can include Bluetooth wireless communication circuit, microprocessor, electronic memory, and sensors (such as thermometers, accelerometer, light sensor, microphone, speaker, etc.) The DM device can be linked to a user's 302 smartphone, or the user's sleep monitor 10 via a Bluetooth communication link. The DM device can be positioned next to the user's sleeping partner, as the partner sleeps. The sensors of the DM device will record various measurements and the processor will store the measurements, along with time and date information on the local memory. The DM device uploads its collected data, at prescribed times (preferably the next morning) to either the user's smartphone or to the user's sleeping monitor. The data is then later compared with the sleep data collected by the sleep monitor and the smartphone of the user, synched by time. In this manner, if the user has any sleep issues during a particular night, the data from the DM device 300 (representing the sleep partner) may be reviewed to determine if the user's sleep event was influenced by the real partner's movements, sound, or temperature.

For example, if the user's sleep data shows a disruption event at 3:35 AM where she is awakened from a light stage of sleep, and data collected from her sleep partner shows sudden movement at exactly 3:35 AM, then a correlation between her disruption and his movement at 3:35 AM may be assumed. If this type of disturbance occurs regularly, then corrective action may be necessary to ensure that the user's sleep quality is at least maintained or even improved. One possible corrective action could be to monitor the sleep of the user's partner to determine why he is moving so much while sleeping. When the user's partner's sleep issues are corrected, the user's sleep will benefit. Other corrective actions may include the use of separate beds.

It is appreciated that the monitor device shown in FIGS. 1-4 can also be configured to implement the functions described herein by the DM device. In that regard, the DM device 300 can be considered a specific embodiment of a sleep monitor device as contemplated by the present disclosure.

According to the present invention, the DM device may also be used to measure vibration, temperature and noise disturbances of a user's partner, when the user is not present in the same bed. In this manner, the DM device is preferably positioned in the location of the user in the bed while the user is absent, i.e., in place of the user. In use, in this arrangement, according to this embodiment of the invention, as the user's partner sleeps, the DM device will measure and record the movements of the bed, the temperature of the bed and the sounds from the bed, as felt and heard from the user's position in the bed. Using the DM device in this manner, the user may determine in advance the types of potential disturbances he or she can expect when the user returns to sleep in the same bed. This method of effectively replacing a user with the DM device may also be used when testing out a new mattress at a mattress store to measure and record movements (and also temperature and noise) which migrate across the mattress to predict how movement much potential disruption one partner will experience in response to movement of the other.

The DM device may be used to compare movements of a new mattress with movements already recorded using an old mattress to determine if there are any meaningful differences, for better or worse. In testing, prior to going to the mattress store, the DM device (or a smartphone running a software program) may first be positioned on one side (e.g., the left side) of the user's home “old” mattress, and in a known orientation. The user, lying down on an opposing side (e.g., right side) of the old mattress is instructed to switch sleeping positions from sleeping on his or her right side to his or her left side, and also moving from prone to supine positions, and other combination of movements, following a prescribed pattern. According to the invention, DM device itself may instruct the user during use, by electronically announcing (generating a synthetic voice through speaker) how the user should move around in bed during the initial testing. Alternatively, the DM device may link by Bluetooth to the user's smartphone, and work with a running software program which would instruct the user how to move in bed during the initial test. Finally, according to another aspect of the invention, the function of DM device may be provided entirely in the user's smartphone as a running software program wherein sensors already provided on smartphones are used to measure specific characteristics of an environment, such as vibration, light, and sound. Regardless of whether the DM device or a smartphone with a running software program is used, the user then visits a mattress store and performs the same test using a select new mattress, following the same sequence of movements as before. The data recorded during test using the new mattress can be readily compared with the data recorded using the old mattress. Using the DM device in this manner, the user may understand how a new mattress will perform during sleep movements compared with an old mattress. Owing to the expense and effort one typically spends when replacing an old mattress with a new one, this information can be very useful.

According to another embodiment of the present invention, the DM device may be modularly connected to sleeping monitor (functioning as a base station), as a removable modular component. When mechanically connected, the modular DM device preferably includes electrical connection as well so that the battery of the DM device may be automatically recharged by power from the sleeping monitor and data may flow between the memory components of both. In this arrangement, a user may detach the DM device whenever it is needed and return the device to the sleeping monitor for convenient storage.

Also, and alternatively, the above-described DM device may be effectively substituted using a software program and a user's smartphone. In such instance, the accelerometer sensor and microphone already present in most smartphones may be instructed by the running software program to pick up local movement and sounds and store the data, synched to date and time. The software program may then upload the data to another device or server for analysis or comparison, or may be used directly on the screen to determine if any movements or sounds occurred at a specific time of interest.

According to another one embodiment of the present invention, the present system is able to automatically recognize when sleeping aids are introduced into the user's bedroom, used by the user during sleep and what the actual products are. According to this embodiment of the invention, and with permission from the user, the system accesses order information from either the website used by the user to purchase such items, such as Amazon.com, or the payment information used to purchase items by the user, such as VISA, or PayPal. For example, during initial setup of the system by the user, the user optionally inputs purchase information, such as credit card account information, or PayPal account information and agrees to use the inputted payment method when purchasing sleep-related items. In this manner, the present system can monitor purchases made by the user and flag any products that fit pre-defined criteria, such as the purchase of pillows, mattresses, sheets, sound-generators, humidifiers, etc. Upon detection of such a product purchase, the present system sends a simple inquiry to the user by text, email or other regarding the purchase, such as: “We noticed that you recently purchased a new “COOLER-HEADS” pillow, by Pillow-Matic.com—Is this pillow for you?” If yes, the present system automatically inserts a “PRODUCT NOW IN USE” button using the present software program so that it appears on the user's smartphone screen each night. The user is instructed to press the “PRODUCT NOW IN USE” button when the user begins using the new product during his or her sleep. In this manner, the present system will be able to associate future monitored sleep data of the user with the new product, once the user presses the button. For example, if, after using the new pillow, in the above example, the present monitor shows improved sleep data, the present system would credit the improved results to the new product. It is contemplated that the present system could ask the user to switch back to the old pillow for one night to see if the user's sleep parameters return to the pre-new product period. If so, then the new product will be graded highly, regarding improving the sleep behavior of the particular user. The system can then confirm on an accessible database of product reviews that the particular pillow was able to improve the sleep of a specific user (having specific characteristics and conditions). All identification information would preferably remain private.

Alternatively, instead of the present system accessing the user's payment information to determine when a new sleep aid product has been purchased, the present system may link to the user's email and monitor for “Order Confirmation” email and/or “Ship Notification” email and search for terms that indicate the purchase of a sleep aid. The present system may again ask the user to confirm what the particular sleep aid product is and if it is for their specific use, and again confirm when the user begins to user the new product, as mentioned above. In place of using a “ NOW IN USE” button, as described above, the present system may use the ship notification information uncovered in the user's email to estimate when the product arrives and make assumptions as to when the user begins to use the new product, such as within a couple of days of receiving the product. The system may then analyze monitored sleep data from that point on looking for noticeable changes in sleep data of the user. If the product makes a difference, then the sleep data will show a difference.

According to another one embodiment of the invention, the present system may simply rely on the user to inform the system, through the system's software program when a new sleep aid product is going to be used by the user during sleep. In such instance, the system may instruct the user to input the product details of the new product (brand name, model number, SKU, etc.) or ask the user to scan the product's bar code using the camera of the smartphone. This will allow the system to ensure that accurate product details are inputted. As before, the new product will effectively be tested by the present system by having the system associate future monitored sleep data of the user to the new product. The new product will either improve the sleep quality, worsen the sleep quality, or make no meaningful difference.

According to another one embodiment of the invention (not shown), a new product includes an integral BLE beacon. The present system uses monitor, such as monitor 10, described above, located next to the user's bed to automatically detect the beacon's presence when the product is moved to within a prescribed distance of the monitor.

When the monitor detects a beacon, the beacon is automatically interrogated for identifying information, thereby determining the details of the new product. In this embodiment, a Bluetooth transmitter/receiver circuit suitable for detecting and communicating with low-energy Bluetooth (BLE) devices would be included in the sleep monitor located on the side table of the user's bed. Once a new product is detected, by reading the product's BLE beacon, the present system would ask the user to confirm (using the present software program) the details of the new product and if the product is meant for use by the user, or by someone else. Instead of using the monitor, or in addition to using the monitor, the present system may include a scanning device positioned at any appropriate location in a user's bedroom, such as at the bedroom's doorway, to automatically scan for new products passing therethrough. Also, if a BLE beacon is installed within a mattress and the BLE includes a built-in accelerometer or other directional sensor, the present system will be able to detect the presence of the new mattress through detection and communication with the BLE and the orientation of the mattress, as well as which side the mattress is facing. The present system can use his information to remind the user to rotate and/or flip the mattress after a prescribed period of time has elapsed, such as 6 months. This will help the mattress maintain its shape and firmness. Regardless, if a user's sleep quality degrades overtime, the present system may recommend that the user flip his or her mattress anyway to see if doing so will improve the quality numbers. If it does, the system will remind the user to continue doing so on a regular schedule. Also, the present system may offer a courtesy reminder to the user to wash his or her bedding following a schedule to ensure clean sheets and pillow cases, which can only encourage a healthy lifestyle. A reminder to replace a pillow may also be scheduled since most pillows lose their structural firmness over time and can also accumulate mites.

The present system may detect sudden changes in a person's sleep quality and increased movement throughout the night and make assumptions that the user may be sick. The system may inquire of the user's health and ask the user to confirm. If the user confirms that he or she has the Flu, for example, the present system may record the “signature” of the monitored data for the next few days, while the user remains sick. This information may then be stored and used for future recognition of the user being sick and used to help decide when the user should be reminded to wash the bedding when his or her sleep-monitored data show signs of returning to “normal.” Of course, washing the bedding will help reduce the chances of reinfection.

If the newly acquired sleep aid product is an IOT device, such as a NEST brand thermostat, Google Home device, or a Philips brand smart light bulb, then the present system will automatically recognize the new device when it is installed and connected with the home network.

Regardless of how a new product is detected, the system, according to another embodiment of the present invention, will be able to connect with the Internet through the home network and retrieve the product warranty and return details from the retailer from which the user purchased the product. The present system can then remind the user of critical return dates of the new product before reaching them. According to the invention, reminding the user about the product's return information may be automatic, or may only be in response to the present system determining through sleep monitoring that the new product is not helping the user improve his or her sleep quality.

As mentioned above, overtime the present system will begin to learn a user's sleep habits and his or her monitored sleep data may show predictable patterns. Should a parameter or several parameters of a user's sleep data change relatively suddenly, the present system will inquire of the user if the user made any recent changes to his or her behavior, including exercise, work stress, an increased or decreased consumption of alcohol, caffeinated drinks, drugs, tobacco products, or food. If the user confirms that nothing has changed, then the system may inquire if a sleep-related product has been replaced or is no longer being used, such as the recent use of a new pillow, etc.

According to the invention, the present system is designed to automatically analyze monitored data of a user and compare the data with known data “signatures” of known conditions of stored data from other monitored users. For example, if the monitored data from a subject user has signature data points that are similar to other, previously monitored users and such data points are associated with a sleep apnea condition, then the present system would be able to consider that the present user may be suffering from a similar sleep apnea condition. In this example, based on the similarities of newly monitored data with known data, the present system can offer suggestions to the user on how to treat or mitigate sleep apnea, with a certain level of confidence, automatically. Depending on the recognized condition, assuming the system is able to match the current user's sleep data with a known data condition, the recommendations provided by the present system may be one of a product, a service, and a medical treatment.

The recommendation may match what was recommended from previous users having common data points and common conditions, or may include new, updated recommendations, based on new products or research, depending on the condition itself.

The present system preferably continuously analyzes a user's monitored data, looking for trends and data point signatures that match known conditions. If there are no matches found, the system may recommend certain products or services which may help improve the user's overall sleep quality, as shown to be the case when the products have been used with other subscribers which similar user parameters (age, gender, height, weight, level of exercise, etc.). If a data point “signature” to a known sleep condition is uncovered over a period of time, depending on the particular condition, the subject user may or may not be immediately given a recommendation. For example, if the user's data points suggest that the user likely needs a new pillow, the present system may offer the suggestion after additional data is acquired to ensure that this is indeed the case. However, if the user's data points suggests a condition such as sleep apnea (wherein the monitored data of the user reveals excessive loud snoring when in the supine position and noticeable leg jerk movements at a certain sleep stage level), the level of concern increases and the present system quickly suggest immediately medical intervention to confirm and treat the condition, since sleep apnea is potentially life-threatening and often overlooked.

The present system may offer a hierarchical pattern of suggestions to overcome a user's recognized sleep-related condition. In this arrangement, the system will first offer a first level of solution, perhaps a product suggestion, and then, if the user's sleep quality shows no improvement, offer a next level of solution, and so on, until the monitored data shows improvement. In each case, the user's sleep is carefully monitored and the collected data analyzed, as before. The time between suggestions may be days, weeks, or however long is required to establish any net affect on a user's sleep pattern or sleep quality. The present system will select suggestions according to predetermined parameters and factors, such as cost of implementing the suggestion, potential risk of implementing the suggestion, and level of confidence of the detected condition, among others. For example, a user's monitored sleep data shows a pattern that is similar to other people who ended up having a stiff neck from sleeping. A first level suggestion, in this example, is to get a neck massage and a second level suggestion is to purchase a relatively expensive memory-foam pillow. Normally, the present system would offer to the user the first level suggestion first, but in this example, the system learns of a sale of a particularly highly rated (as determined by a history of good user reviews) memory-foam pillow, which is ending soon. Because there is a cost savings and the level of risk of implementing either the level one or the level two suggestion is low, the present system would offer to the user the second suggestion first, indicating where the user may purchase the pillow at reduced cost.

It is contemplated that companies of products may request access to the present system, as a marketing effort, to target specific groups of users to use their products to overcome certain sleep-related conditions. Depending on the sleep-related condition and promotion details, the present system can implement the promotion for those users which fit the designated or targeted group and encourage a suggestion to overcome a specific sleep condition that promotes the particular product of the participating company. For example, a brand name mattress company wants to promote their top-tier mattress to couples in their 30's who live in the Denver area and the company will offer 30% off the price of the mattress to the first 100 couples that match the targeted group. The present system can help monitor the users in the Denver area who meet the criteria and offer the company's promotion details for those users who are shown by their monitored sleep data to have a sleep-issue wherein one suggestion would be to purchase a new firm mattress. In such instance, the present system would suggest the mattress of the promotion and would include the sale details. The present system would only do this if the promoted product would indeed align with a genuine suggestion for improvement for the particular user.

According to yet another one embodiment of the present invention, the present system may monitor a user's sleep and suggest that the user stay at a specific nearby hotel which includes specific known rooms which have been effectively certified to meet specific sleep requirements. These include a firm new bed, quiet location in town, double-pane windows, soundproof walls, blackout drapes, soft music, etc. The system would suggest that the user stay at such a location for a period of time as a “sleep-reset.” Sleeping in a room filled with beneficial sleep-aids may also help the user test out certain products which may encourage the user to later purchase for use in his or her home setting.

According to yet another one embodiment of the present invention, the present system monitor a user while he or she sleeps. The present system can determine by the movement signatures and sounds of the user which stage of sleep the user has reached and can also determine when the user awakens. According to this embodiment, the monitor has control over IOT devices and can activate specific devices in response to the user entering a certain stage of sleep or becoming awake. For example, if it is known that a male user enjoys classical music because it calms him down and helps him go to sleep, the monitor can use this information to automatically activate a music player (connected either directly or wirelessly to the monitor) to play classical music when the monitor determines that the user has just awakened. The music will start softly and increase slowly in volume to a preset level. The music will help the user quickly return to sleep. The monitor may also control lights in the room and air conditioning devices (hot, cold, humidity, etc.) in response to detection that the user reaches a specific stage of sleep, not only waking up. If a user is known to often reside in the first stage of sleep (light sleep) for long periods of time, the monitor of the present invention can change an environment factor, such as introducing soft, quiet music to encourage the user to reach a deep stage of sleep. It is contemplated a sleep monitor be provided with an integral music player and speaker and a courteously light or even a reading light so that wireless connections to TOT devices do not have to be made.

According to another one embodiment of the present invention, and referring to FIG. 4, in situations where two people are sleeping in a common bed, each person has a dedicated sleep-monitor radar transducer 226, 232, and each has a smartphone located on their respective side table. According to this embodiment, the present system is able to use all the sensors of each smartphone to help understand the sleep behavior of each person in bed, how the movements and sounds of each person affects the other, and also to help better understand the bedroom environment. The present system activates the microphone of a left-side person's smartphone, for example, and listens to that person's sleep sounds, such as snoring. The present system correlates the picked-up snoring sounds with the detected sleep movements (and sounds) of not only the person sleeping on the left-side, but also, of the person sleeping on the right-side of the bed. One partner may snore, and when he or she does, the present system may detect increased movement and a change of sleep stage of the other partner. Owing to the timing of both events and perhaps the lack of additional potential disturbances in the bedroom, the present system would identify the snoring partner as the source of sleep-disturbance of the disturbed partner.

According to the invention, the smartphone of either user may be activated one at a time, alternating, or together at the same time. When both smartphones are being used simultaneously, the present system can better “listen” for sounds reaching or emanating from the bedroom. By activating the microphones of nearby smartphones, the present system can expand the effective range of recorded audio and provide directional information which may help the present system better locate the source of any captured sound (through triangulation techniques). The present system can link with, and preferably control the use of any peripheral device, including smartphones, various TOT devices, including medical devices, such as a user's continuous positive airway pressure (CPAP) machine to collect data (and metadata) relating to either the user of the present system, or the user's environment, in particular, the user's bedroom.

Other sensors, including sleep-monitoring devices may be used to correlate movements by one partner with signs of sleep-disruption of the other. For example, a left-side sleep partner may suffer from occasional Restless-Leg-Syndrome, and when such an event occurs, the user's sleep monitor will detect it. Following this example, the right-side sleep monitor detects sudden and unusual movement and sound from the right-side sleeping partner immediately after detection of the left side user's leg movement event. The present system connects the two events and establishes cause and effect evidence and notifies both partners, providing suggested remedies. Other sleep issues may be detected as well, such as snoring and bruxism (teeth grinding).

It is to be understood that any data collected by the present system, including by any sleep-monitor or smart device operating within the present system including metadata related to the data and that the present system may receive or otherwise collect any type of data from any type of electronic device, including any TOT device and any sensor.

Herein, “or” is inclusive and not exclusive, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A or B” means “A, B, or both,” unless expressly indicated otherwise or indicated otherwise by context. Moreover, “and” is both joint and several, unless expressly indicated otherwise or indicated otherwise by context. Therefore, herein, “A and B” means “A and B, jointly or severally,” unless expressly indicated otherwise or indicated otherwise by context.

This disclosure encompasses all changes, substitutions, variations, alterations, and modifications to the example embodiments herein that a person having ordinary skill in the art would comprehend. Moreover, although this disclosure describes and illustrates respective embodiments herein as including particular components, elements, functions, operations, or steps, any of these embodiments may include any combination or permutation of any of the components, elements, functions, operations, or steps described or illustrated anywhere herein that a person having ordinary skill in the art would comprehend. Furthermore, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative. 

1. A computer-implemented method for recommending a sleep-aid product for a user, comprising: monitoring the user's sleep to thereby obtain monitoring data; by using at least one computer processor, analyzing the monitoring data and identifying at least one issue with the user's sleep; and by using at least one computer processor and based on the analysis, providing a recommendation on a sleep-aid product for the user on an electronic device user interface that addresses the at least one issue.
 2. The method of claim 1, wherein analyzing the monitoring data comprising determining the effect of one or more products being currently used by the user on the user's sleep.
 3. The method of claim 1, further comprising: monitoring the user's sleep for a preset period of time after the user starts using the recommended sleep-aid product to obtain updated monitoring data; by using at least one computer processor, analyzing the updated monitoring data; based on the analysis and by using at least one computer processor, determining the effect of the recommended sleep-aid product on the user's sleep.
 4. The method of claim 1, wherein the recommendation is based on databases containing products and their alleged benefits on a user's sleep.
 5. The method of claim 1, further comprising: providing one or more questions for the user to answer regarding the user's experience with the use of the recommended product, and receiving a response from the user; wherein the determination is further based on the user's response.
 6. The method of claim 5, further comprising: generating, using at least one computer processor, a quantitative effectiveness score for the recommended product based on the monitoring data.
 7. The method of claim 6, further comprising: generating, using at least one computer processor, an overall effectiveness score for the recommended product based on both the monitoring data and the user's response.
 8. The method of claim 7, wherein generating the overall effectiveness score comprises discounting the user's response distorted by secondary factors not directly relating to the performance of the recommended product.
 9. The method of claim 1 any of the foregoing claims, wherein the monitoring the user's sleep comprising monitoring the user's body movements during the sleep.
 10. The method of claim 1 any of the foregoing claims, wherein the monitoring the user's sleep comprising monitoring an environmental condition during the user's sleep in the room where the user sleeps.
 11. The method of claim 1, further comprising: uploading the monitoring data to a remote server.
 12. A computer-implemented method for evaluating the effectiveness of a sleep-aid product for a user's sleep, comprising: monitoring the user's sleep to thereby obtain monitoring data, wherein during the user's sleep the sleep-aid product is being used; by using at least one computer processor, analyzing the monitoring data with respect to a known issue of the user's sleep; and based on the analysis and by using at least one computer processor, determining the effectiveness of the sleep-aid product on addressing the issue in the user's sleep.
 13. The method of claim 12, further comprising: monitoring the user's sleep before the user uses the sleep-aid product to obtain first collected data; wherein determining the effectiveness of the recommended sleep-aid product is at least partially based on comparing the monitoring data with the first collected data. 14.-18. (canceled)
 19. A computer-implemented method for evaluating the effectiveness of a sleep-aid product for a user's sleep, comprising: monitoring the user's sleep to thereby obtain baseline monitoring data; determining when the user has acquired and started using a new sleep-aid product; monitoring the user's sleep while the new sleep-aid product is being used, to thereby obtain updated monitoring data; and by using at least one computer processor, comparing the updated monitoring data with the baseline monitoring data, to thereby determine the desirability of the sleep-aid product.
 20. The method of claim 19, wherein determining when the user has acquired and started using a new sleep-aid product comprises: tracking the user's online purchase history.
 21. The method of claim 19, wherein determining when the user has acquired and started using a new sleep-aid product comprises: presenting one or more questions to the user on an electronic device user interface and receiving the user's response thereto. 